Active learning in a real-world bioengineering problem: A pilot-study on ophthalmologic data processing

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Abstract

Active learning is a format alternative to the conventional lecture/recitation/ laboratory; research results have reported that it is suitable to encourage student inquiry and foster peer mentoring. Although the availability of computer-based learning materials in biomedical sciences is increasing, there are relatively few studies aimed to integrate traditional methods of teaching with inquiry-based approaches utilizing these Information and Communication Technologies (ICT) tools. This paper describes a pilot-study on a comprehensive active laboratory course about digital ophthalmologic signal classification, experienced by a group of undergraduates in Bio-Electronic Engineering. During the activity, the students became able to discriminate healthy subjects from patients affected by two retinal pathologies: Achromatopsia or Congenital Stationary Night Blindness. The study was based on the analysis and classification of the electroretinograms, that record the retinal response to a light flash. To process electroretinographic data, a software based on the Empirical Mode Decomposition and an Artificial Neural Network was used. Our findings indicate that this laboratory experience can be considered effective in improving student's reasoning skills and that students acting as investigators achieve a better outcome, presumably because this activity satisfies their psychological needs for autonomy, competence, and relatedness.
Lingua originaleEnglish
pagine (da-a)485-499
Numero di pagine15
RivistaComputer Applications in Engineering Education
Volume27
Stato di pubblicazionePublished - 2019

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Engineering(all)
  • Education

Cita questo

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title = "Active learning in a real-world bioengineering problem: A pilot-study on ophthalmologic data processing",
abstract = "Active learning is a format alternative to the conventional lecture/recitation/ laboratory; research results have reported that it is suitable to encourage student inquiry and foster peer mentoring. Although the availability of computer-based learning materials in biomedical sciences is increasing, there are relatively few studies aimed to integrate traditional methods of teaching with inquiry-based approaches utilizing these Information and Communication Technologies (ICT) tools. This paper describes a pilot-study on a comprehensive active laboratory course about digital ophthalmologic signal classification, experienced by a group of undergraduates in Bio-Electronic Engineering. During the activity, the students became able to discriminate healthy subjects from patients affected by two retinal pathologies: Achromatopsia or Congenital Stationary Night Blindness. The study was based on the analysis and classification of the electroretinograms, that record the retinal response to a light flash. To process electroretinographic data, a software based on the Empirical Mode Decomposition and an Artificial Neural Network was used. Our findings indicate that this laboratory experience can be considered effective in improving student's reasoning skills and that students acting as investigators achieve a better outcome, presumably because this activity satisfies their psychological needs for autonomy, competence, and relatedness.",
author = "Leonardo Bellomonte and {Persano Adorno}, Dominique",
year = "2019",
language = "English",
volume = "27",
pages = "485--499",
journal = "Computer Applications in Engineering Education",
issn = "1061-3773",
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TY - JOUR

T1 - Active learning in a real-world bioengineering problem: A pilot-study on ophthalmologic data processing

AU - Bellomonte, Leonardo

AU - Persano Adorno, Dominique

PY - 2019

Y1 - 2019

N2 - Active learning is a format alternative to the conventional lecture/recitation/ laboratory; research results have reported that it is suitable to encourage student inquiry and foster peer mentoring. Although the availability of computer-based learning materials in biomedical sciences is increasing, there are relatively few studies aimed to integrate traditional methods of teaching with inquiry-based approaches utilizing these Information and Communication Technologies (ICT) tools. This paper describes a pilot-study on a comprehensive active laboratory course about digital ophthalmologic signal classification, experienced by a group of undergraduates in Bio-Electronic Engineering. During the activity, the students became able to discriminate healthy subjects from patients affected by two retinal pathologies: Achromatopsia or Congenital Stationary Night Blindness. The study was based on the analysis and classification of the electroretinograms, that record the retinal response to a light flash. To process electroretinographic data, a software based on the Empirical Mode Decomposition and an Artificial Neural Network was used. Our findings indicate that this laboratory experience can be considered effective in improving student's reasoning skills and that students acting as investigators achieve a better outcome, presumably because this activity satisfies their psychological needs for autonomy, competence, and relatedness.

AB - Active learning is a format alternative to the conventional lecture/recitation/ laboratory; research results have reported that it is suitable to encourage student inquiry and foster peer mentoring. Although the availability of computer-based learning materials in biomedical sciences is increasing, there are relatively few studies aimed to integrate traditional methods of teaching with inquiry-based approaches utilizing these Information and Communication Technologies (ICT) tools. This paper describes a pilot-study on a comprehensive active laboratory course about digital ophthalmologic signal classification, experienced by a group of undergraduates in Bio-Electronic Engineering. During the activity, the students became able to discriminate healthy subjects from patients affected by two retinal pathologies: Achromatopsia or Congenital Stationary Night Blindness. The study was based on the analysis and classification of the electroretinograms, that record the retinal response to a light flash. To process electroretinographic data, a software based on the Empirical Mode Decomposition and an Artificial Neural Network was used. Our findings indicate that this laboratory experience can be considered effective in improving student's reasoning skills and that students acting as investigators achieve a better outcome, presumably because this activity satisfies their psychological needs for autonomy, competence, and relatedness.

UR - http://hdl.handle.net/10447/349454

UR - https://onlinelibrary.wiley.com/doi/10.1002/cae.22091

M3 - Article

VL - 27

SP - 485

EP - 499

JO - Computer Applications in Engineering Education

JF - Computer Applications in Engineering Education

SN - 1061-3773

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